“The leverage” to do what exactly? Put in someone who will be way worse? How does that help the left accrue power or accomplish our goals? If you think the Democratic Party’s takeaway from the left tanking a major election will be “we need to move left more” I have a bridge to sell you. We are not a majority, which means we need to form coalitions. We can’t do that with a reputation of blowing up everyone’s shit when we don’t get our way. We do it by showing how successful the party is when they listen to us and include us. No, this time we don’t have a particularly left candidate to vote for. Yes, it all sucks. But I have yet to see a concrete explanation of how picking or allowing “far right fascist” over “moderate” has any benefit in the short or long term. To my eyes, it just causes vulnerable people here and around the world to suffer.

The UN is supposed to be a toothless, executively dysfunctional institution, that’s a feature, not a bug. Its members are nations, whose entire purpose is to govern their regions of the planet. If the UN itself had the power to make nations do things, it wouldn’t be the United Nations, it’d be the One World Government, and its most powerful members absolutely do not want it to be that, so it isn’t.

It’s supposed to be an idealized, nonviolent representation of geopolitics that is always available to nations as a venue for civilized diplomacy. That’s why nuclear powers were given veto power: they effectively have veto power over the question of “should the human race continue existing” and the veto is basically a reflection of that. We want issues to get hashed out with words in the UN if possible, rather than in real life with weapons, and that means it must concede to the power dynamics that exist in real life. The good nations and the bad nations alike have to feel like they get as much control as they deserve, otherwise they take their balls and go home.

It’s frustrating to see the US or Russia or China vetoing perfectly good resolutions and everyone else just kind of going “eh, what can you do, they have vetoes,” but think through the alternative: everyone has enough and decides “no more veto powers.” The UN starts passing all the good resolutions. But the UN only has the power that member nations give it, so enforcement would have to mean some nations trying to impose their will on the ones that would’ve vetoed. Now we’ve traded bad vetoes in the UN for real-world conflict instead.

What that “get rid of the vetoes so the UN can get things done” impulse is actually driving at is “we should have a one world government that does good things,” which, yeah, that’d be great, but it’s obviously not happening any time soon. Both articles mention issues and reforms that are worthy of consideration, but the fundamental structure of the UN is always going to reflect the flaws of the world because it’s supposed to do that.

“Lossless” has a specific meaning, that you haven’t lost any data, perceptible or not. The original can be recreated down to the exact 1s and 0s. “Lossy” compression generally means “data is lost but it’s worth it and still does the job” which is what it sounds like you’re looking for.

With images, sometimes if technology has advanced, you can find ways to apply even more compression without any more data loss, but that’s less common in video. People can choose to keep raw photos with all the information that the sensor got when the photo was taken, but a “raw” uncompressed video would be preposterously huge, so video codecs have to throw out a lot more data than photo formats do. It’s fine because videos keep moving, you don’t stare at a single frame for more than a fraction of a second anyway. But that doesn’t leave much room for improvement without throwing out even more, and going from one lossy algorithm to another has the downside of the new algorithm not knowing what’s “good” visual data from the original and what’s just compression noise from the first lossy algorithm, so it will attempt to preserve junk while also adding its own. You can always give it a try and see what happens, of course, but there are limits before it starts looking glitchy and bad.

Homophobia and transphobia, when you dig into them a bit, are often based in a fear that they’ll be on the other end of toxic masculinity instead of the one they’re used to.

Archive Team often uses the Internet Archive to share the things they save and obviously they have a shared goal of saving a copy of everything ever made, but they aren’t the same people. The Archive Team is a vigilante white hat hacker group (well, maybe a little bit grey), and running a Warrior basically means you’re volunteering to be part of their botnet. When a website is going to be shut down, they’ll whip together a script and push it out to the botnet to try to grab as much of the dying site as they can, and when there’s more downtime they have some other projects, like trying to brute force all those awful link shorteners so that when they inevitably die, people can still figure out where it should’ve pointed to.

I know TiddlyWiki quite well but have only poked at Logseq, so maybe it’s more similar to this than I think, but TiddlyWiki is almost entirely implemented in itself. There’s a very small core that’s JavaScript but most of it is implemented as wiki objects (they call them “tiddlers,” yes, really) and almost everything you interact with can be tweaked, overridden, or imitated. There’s almost nothing that “the system” can do but you can’t. It’s idiosyncratic, kind of its own little universe to be learned and concepts to be understood, but if you do it’s insanely flexible.

Dig deep enough, and you’ll discover that it’s not a weird little wiki — it’s a tiny, self-contained object database and web frontend framework that they have used to make a weird little wiki, but you can use it for pretty much anything else you want, either on top of the wiki or tearing it down to build your own thing. I’ve used it to make a prediction tracker for a podcast I follow, I’ve made my own todo list app in it, and I made a Super Bowl prop bet game for friends to play that used to be spreadsheet-based. For me, it’s the perfect “I just want to knock something together as a simple web app” tool.

And it has the fun party trick (this used to be the whole point of it but I’d argue it has moved beyond this now) that your entire wiki can be exported to a single HTML file that contains the entire fully functional app, even allowing people to make their own edits and save a new copy of the HTML file with new contents. If running a small web server isn’t an issue, that’s the easiest way to do it because saving is automatic and everything is centralized, otherwise you need to jump through some hoops to get your web browser to allow writing to the HTML file on disk or just save new copies every time.

If you run the Node.js version, that’s all handled for you. It’s only if you want to do the party trick of keeping it all in a single HTML file that you need to worry about a plugin or anything like that. And even then, the server version exports to a standalone HTML file with one or two clicks.

Edit to add: it’s the only substantial Node package I’ve ever seen with zero dependencies. Very lightweight and simple to run.

Ooh, interesting. I’m kind of surprised to find that I do feel more comfortable with It/Its actually, not so much because of the logical “promotion and demotion cancel out” aspect, but because it’s two atypical constructions combined, and that almost pushes it out of intuitive meaning entirely for me. I know the context and convention for each one individually but nothing for both of them at the same time, so I think I’m more open to allowing a meaning to be defined that isn’t hierarchical if It assures me that it isn’t. (Pure grammar bonus points in that last sentence where this type of capitalization happens to remove an ambiguity!) For He/Him and She/Her, though, I find it hard to set aside the established meaning because it’s in wide use and has been for quite some time. Maybe that’s a rigidity that deserves to be bent, people push back on the more “out there” neopronouns for similar reasons, but I think it’s likely that most people will instinctively react negatively when encountering this, and it’s going to be difficult for what I have to imagine is a very small group of people to change the general understanding to something more acceptable.

Hmm… this makes me uncomfortable, and although I don’t think it’s internalized phobia or anything like that, I want to interrogate that discomfort to see if I can nail it down.

I do think it’s difficult or maybe impossible to decouple this practice from indications of power for most people. The only instances of capitalized pronouns in common use that I’ve seen are the God and Jesus usage, and in some circles, capitalizing pronouns for a dominant in a role play context. “I” getting capitalized is also there, kind of, but that’s not a power thing because it’s not special, everyone is expected to use it as a language rule. I’ve also seen things like “oh, sure, that’s what They want you to think” or, not quite a pronoun, something like “they want you to fear The Other,” maybe less of a power thing but definitely a signal of additional weight and meaning above and beyond the word’s usual sense.

I think this is the main source of my discomfort, that this practice is currently used almost exclusively at least as “this word is being used in a special and important context, pay extra attention” and going as far as “I am explicitly signaling that the person being referred to is superior.” I don’t use He/Him pronouns for God or Jesus because I don’t belong to those religions and don’t see those entities that way, and I have a fundamental belief in the equality of all humans that makes me uncomfortable putting a person on a pedestal like that.

I feel uncomfortable about it/its pronouns as well for the same reason, I don’t like the idea of dehumanizing or objectifying a person, but in that case I actually have some friends who use them. It’s easier to take a “well, if it makes you happy, it’s no harm to me” attitude if it’s asking for a “demotion” so to speak, I think. The personal connection probably does help too, I don’t know anyone who wants capitalized pronouns myself.

I’ve seen Dan Savage use capital pronouns to refer to dominants when answering letters, but that seems to me like Dan stepping into the letter writer’s scene space and choosing to go along with the “rule” while he’s there giving advice, kind of a “good houseguest” thing. I don’t think that’s something that the rest of us are obligated to do as a rule. I’d push back on a friend insisting that I refer to their dominant with capitalized pronouns, because whatever their relationship is with each other, their dom isn’t my dom, and I didn’t agree to that hierarchy, they did.

I think the other discomfort is more of a language and grammar thing, which obviously is less important than an actual person’s comfort (see also, the old “they is always plural” chestnut) so I’m not going to assert that this is a reason to disregard a person’s wishes, and language rules are subject to change. But in general capitalization is not all that significant in English, which we know because something written in all caps or in all lower case usually has no meaning removed. Words at the start of sentences, proper nouns, and “I” get capitalized, and that’s mostly it. It’s mostly about readability, because ALL CAPS DOESN’T HAVE AS MUCH CONTRAST but when used sparingly as we usually do, important words stand out with a capital letter. “Demanding” that a particular word be used to refer to yourself in the form of pronouns is in the same ballpark as choosing your own name, obviously completely reasonable and acceptable, but “demanding” that special language rules be used about yourself feels a step beyond that. I don’t want to cross into “oh so could you identify as an attack helicopter too” territory, but I do wonder about some of the boundaries on this. Lots of people habitually write in all lowercase, would it be disrespectful to say “oh yeah i saw larry at the empire state building and had a conversation with him” if Larry uses He/Him pronouns? Would Larry be upset about both the name and pronouns, or just the pronouns? I don’t think most people would get up in arms about their proper name getting de-capitalized in that context which seems like further evidence that capitalization isn’t normally a meaningful aspect of the writing, it’s a more mechanical and practical rule, so insisting that for certain people it does need to be made significant feels like more of an imposition to me, and comes right back to the “you need to treat Me as special and more important” feeling that I have.

OPML files really aren’t much more than a list of the feeds you’re subscribed to. Individual posts or articles aren’t in there. I would expect that importing a second OPML file would just add more subscriptions, but it’d be up to the reader app to decide what it does.

If you ask an LLM to help you with a legal brief, it’ll come up with a bunch of stuff for you, and some of it might even be right. But it’ll very likely do things like make up a case that doesn’t exist, or misrepresent a real case, and as has happened multiple times now, if you submit that work to a judge without a real lawyer checking it first, you’re going to have a bad time.

There’s a reason LLMs make stuff up like that, and it’s because they have been very, very narrowly trained when compared to a human. The training process is almost entirely getting good at predicting what words follow what other words, but humans get that and so much more. Babies aren’t just associating the sounds they hear, they’re also associating the things they see, the things they feel, and the signals their body is sending them. Babies are highly motivated to learn and predict the behavior of the humans around them, and as they get older and more advanced, they get rewarded for creating accurate models of the mental state of others, mastering abstract concepts, and doing things like make art or sing songs. Their brains are many times bigger than even the biggest LLM, their initial state has been primed for success by millions of years of evolution, and the training set is every moment of human life.

LLMs aren’t nearly at that level. That’s not to say what they do isn’t impressive, because it really is. They can also synthesize unrelated concepts together in a stunningly human way, even things that they’ve never been trained on specifically. They’ve picked up a lot of surprising nuance just from the text they’ve been fed, and it’s convincing enough to think that something magical is going on. But ultimately, they’ve been optimized to predict words, and that’s what they’re good at, and although they’ve clearly developed some impressive skills to accomplish that task, it’s not even close to human level. They spit out a bunch of nonsense when what they should be saying is “I have no idea how to write a legal document, you need a lawyer for that”, but that would require them to have a sense of their own capabilities, a sense of what they know and why they know it and where it all came from, knowledge of the consequences of their actions and a desire to avoid causing harm, and they don’t have that. And how could they? Their training didn’t include any of that, it was mostly about words.

One of the reasons LLMs seem so impressive is that human words are a reflection of the rich inner life of the person you’re talking to. You say something to a person, and your ideas are broken down and manipulated in an abstract manner in their head, then turned back into words forming a response which they say back to you. LLMs are piggybacking off of that a bit, by getting good at mimicking language they are able to hide that their heads are relatively empty. Spitting out a statistically likely answer to the question “as an AI, do you want to take over the world?” is very different from considering the ideas, forming an opinion about them, and responding with that opinion. LLMs aren’t just doing statistics, but you don’t have to go too far down that spectrum before the answers start seeming thoughtful.

In its complaint, The New York Times alleges that because the AI tools have been trained on its content, they sometimes provide verbatim copies of sections of Times reports.

OpenAI said in its response Monday that so-called “regurgitation” is a “rare bug,” the occurrence of which it is working to reduce.

“We also expect our users to act responsibly; intentionally manipulating our models to regurgitate is not an appropriate use of our technology and is against our terms of use,” OpenAI said.

The tech company also accused The Times of “intentionally” manipulating ChatGPT or cherry-picking the copycat examples it detailed in its complaint.

https://www.cnn.com/2024/01/08/tech/openai-responds-new-york-times-copyright-lawsuit/index.html

The thing is, it doesn’t really matter if you have to “manipulate” ChatGPT into spitting out training material word-for-word, the fact that it’s possible at all is proof that, intentionally or not, that material has been encoded into the model itself. That might still be fair use, but it’s a lot weaker than the original argument, which was that nothing of the original material really remains after training, it’s all synthesized and blended with everything else to create something entirely new that doesn’t replicate the original.

These models aren’t great at tasks that require precision and analytical thinking. They’re trained on a fairly simple task, “if I give you some text, guess what the next bit of text is.” Sounds simple, but it’s incredibly powerful. Imagine if you could correctly guess the next bit of text for the sentence “The answer to the ultimate question of life, the universe, and everything is” or “The solution to the problems in the Middle East is”.

Recently, we’ve been seeing shockingly good results from models that do this task. They can synthesize unrelated subjects, and hold coherent conversations that sound very human. However, despite doing some things that up until recently only humans could do, they still aren’t at human-level intelligence. Humans read and write by taking in words, converting them into rich mental concepts, applying thoughts, feelings, and reasoning to them, and then converting the resulting concepts back into words to communicate with others. LLMs arguably might be doing some of this too, but they’re evaluated solely on words and therefore much more of their “thought process” is based on “what words are likely to come next” and not “is this concept being applied correctly” or “is this factual information”. Humans have much, much greater capacity than these models, and we live complex lives that act as an incredibly comprehensive training process. These models are small and trained very narrowly in comparison. Their excellent mimicry gives the illusion of a similarly rich inner life, but it’s mostly imitation.

All that comes down to the fact that these models aren’t great at complex reasoning and precise details. They’re just not trained for it. They got through “life” by picking plausible words and that’s mostly what they’ll continue to do. For writing a novel or poem, that’s good enough, but math and physics are more rigorous than that. They do seem to be able to handle code snippets now, mostly, which is progress, but in general this isn’t something that you can be completely confident in them doing correctly. They make silly mistakes because they aren’t really thinking it through. To them, there isn’t really much difference between answers like “that date is 7 days after Christmas” and “that date is 12 days after Christmas.” Which one it thinks is more correct is based on things it has seen, not necessarily an explicit counting process. You can also see this in things like that case where someone tried to use it to write a legal brief, where it came up with citations that seemed plausible but were in fact completely made up. It wasn’t trained on accurate citations, it was trained on words.

They also have a bad habit of sounding confident no matter what they’re saying, which makes it hard to use them for things you can’t check yourself. Anything they say could be right/accurate/good/not plagiarized, but the model won’t have a good sense of that, and if you don’t know either, you’re opening yourself up to risk of being misled.

There just isn’t much use for an approach like this, unfortunately. TypeScript doesn’t stand alone enough for it. If you want to know how functions work, you need to learn how JavaScript functions work, because TypeScript doesn’t change that. It adds some error checking on top of what’s already there, but that’s it.

An integrated approach would just be a JavaScript book with all the code samples edited slightly to include type annotations, a heavily revised chapter on types (which would be the only place where all those type annotations make any difference at all, in the rest of the book they’d just be there, unremarked upon), and a new chapter on interoperating with vanilla JavaScript. Seeing as the TypeScript documentation is already focused on those exact topics (adding type annotations to existing code, describing how types work, and how to work with other people’s JavaScript libraries that you want to use too), you can get almost exactly the same results by taking a JavaScript book and stapling the TypeScript documentation to the end of it, and it’d have the advantage of keeping the two separate so that you can easily tell what things belong to which side.

Protect me from knowing what I don’t need to know. Protect me from even knowing that there are things to know that I don’t know. Protect me from knowing that I decided not to know about the things that I decided not to know about. Amen.

Lord, lord, lord. Protect me from the consequences of the above prayer. Amen.

That’s part of the point, you aren’t necessarily supposed to have an empty mind the whole time. I mean, if you can do that, great, but you aren’t failing if that’s not the case.

Imagine that your thoughts are buses, and your job is to sit at the bus stop and not get on any of them. Just notice them and let them go by. Like a bus stop, you don’t really control what comes by, but you do control which ones you get on board and follow. If you notice that you’ve gotten on a bus, that’s fine, just get off of it and go back to watching. Interesting things can happen if you just watch and notice which thoughts go by, and it’s good practice for noticing what you’re thinking and where you’re going and taking control of it yourself when it’s somewhere you don’t want to go.

When 66 to 72 million years old you reach, look as good you will not, hmm?

This is the key with all the machine learning stuff going on right now. The robot will create something, but none of them have a firm understanding of right, wrong, truth, lies, reality, or fiction. You have to be able to evaluate its output because you have no idea if the robot’s telling the truth or not at that moment. Images are pretty immune to this because everyone can evaluate a picture for correctness or realism, and even if it’s a misleading photorealistic image, well, we’ve already had Photoshops for a long time. With text, you always have to keep in mind that the robot might be low quality or outright wrong, and if you aren’t equipped to evaluate its answers for that, you shouldn’t be using it.

The doom and gloom predictions have always been about slow but inexorable changes in the climate. Not that suddenly a mega hurricane is going to rip Florida out of the ground and toss it into the ocean, but that weather is going to get worse and more extreme, that sea levels will rise, and more and more places will gradually become uninhabitable as conditions get worse. There won’t be single things that you can point to and say “that one was global warming”, it’s about trends that are harmful for us in the long term. If you eat a chocolate bar’s worth more calories than you burn every day, it sounds like doom and gloom to say you’ll gain 200 pounds if you don’t change anything, and you won’t be able to point to any one meal as something to be concerned about because that’s not really out of the ordinary for a day… but slowly and steadily, you’ll gain weight, and if nothing changes you will get there eventually.

And even though you aren’t owed dramatic destruction, and shouldn’t require it to believe the thousands of people who study this as their life’s work and all agree that things are dire and not getting better fast enough… you’ve literally just lived through the hottest twenty or so days in recorded history. Is that a coincidence, do you think?

I hope I don’t come across as too cynical about it :) It’s pretty amazing, and the things these things can do in, what, a few gigabytes of weights and a beefy GPU are many, many times better than I would’ve expected if you had outlined the approach for me 2 years ago. But there’s also a long history of GAI being just around the corner, and we do keep turning corners and making useful progress, but it’s always still a ways off after each leap. I remember some people thinking that chess was the pinnacle of human intelligence, requiring creativity and logic to succeed, and when computers blew past humans at chess, it became clear that no, that’s still impressive but you can get good at chess without really getting good at anything else.

It might be possible for an ML model to assemble itself into general intelligence based solely on being fed words like we’re doing, it does seem like the data going in contains enough to do that, but getting that last 10% is going to be hard, each percentage point much harder than the last, and it’s going to require more rigorous training to stop them from skating by with responses that merely come close when things get technical or precise. I’d expect that we need more breakthroughs in tools or techniques to close that gap.

It’s also important to remember that as humans, we’re inclined to read consciousness and intent into everything, which is why pretty much every pantheon of gods includes one for thunder and lightning. Chatbots sound human enough that they cross the threshold for peoples’ brains to start gliding over inaccuracies or strange thinking or phrasing, and we also unconsciously help our conversation partner by clarifying or rephrasing things if the other side doesn’t seem to be understanding. I suppose this is less true now that they’re giving longer responses and remaining coherent, but especially early on, the human was doing more work than they realized keeping the conversation on the rails, and once you started seeing that it removed a bit of the magic. Chatbots are holding their own better now but I think they still get more benefit of the doubt than we realize we’re giving them.